• (The)Korea Educational Review
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• v.22 no.2
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• pp.133-156
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• 2016

The purpose of this study was to examine the effects of emotion, home environment, school environment on self-regulated learning, focusing on motivational and behavioral regulation. Participants are 2070 students from 95 middle schools of Korean Children and Youth Panel Study(KCYPS). The variables of emotions, home environment, school environment and motivational regulation, behavioral regulation were analyzed using correlation analysis and multiple regression. The results were as follows. First, emotion, home environment, school environment were correlated with on motivational and behavioral regulation. Second, emotion explained motivational regulation and behavioral regulation of self-regulated learning as well as home envionment and school environment. All subvariables of emotion were significantly related to behavior control. Third, among subvariables of home environment, parents education and occupations, and annual household income were not significantly related to motivational regulation and behavioral regulation. However, home economic level perceived by students and parents' interest and abuse on students had great effects. Forth, school environment has a greater explanatory effect on motivational regulation and behavioral regulation. Particularly, friendships and relationships with teachers during learning activities had a significant effect. These results showed that emotion and psychological environment of learning environment are important variables affecting on self-regulated learning and suggests the need for researches on these variables.

• Journal of The Korean Association For Science Education
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• v.35 no.1
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• pp.27-35
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• 2015

General education is changed by accepting the change in education environment to digital generation, emphasis about student-centered education, and change of teacher's role. E-learning has taken center stage as an effective learning environment but the problems are drawn for the absence of interaction that is important in learning. In this study, on the basis of questionnaire results about learning using website, we operated blended-learning where students come and go in cyberspace and physical space to set up the lesson environment for emphasizing interaction. We selected a control group (N=40) and an experimental group (N=40) from second grade students in a middle school for this research. General instructor-led lessons were implemented in the control group and blended-learning lessons to emphasize interaction between teacher and students were implemented in the experimental group. The experiments were applied to eight class-hours in 'characteristics of matter' unit. We implemented Test of Science Related Attitude (TOSRA) to the students before and after the lessons and administered questionnaire for checking attitude changes and perception in students. The results of the test show that the experimental group students were more encouraged and became more confident and curious about scientific learning than the control group students. The analysis of the interview and results of TOSRA show that blended-learning provided guidance and feedback by the teacher to the experimental group students more than the control group students. Blended-learning is suggested as a learning-method that is helpful in improving scientific attitude in students because it enables them to express their experiences without limit of time-space and promote interaction between teacher and students.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.45-52
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• 2016

The purpose of this study was to investigate the meaning of conflict experience in cooperative learning activities of pre-service early childhood teachers. The subjects were 85 pre-service early childhood teachers in W university. The data were collected through unstructured interviews and journal writings of the participants. The study results were as follow. First, pre-service early childhood teacher's conflict experiences in cooperative activity are team meeting, fair participation and evaluation, and conflict of the personal relations. Second, pre-service early childhood teacher's conflict resolution experiences in cooperative activity are autonomy of the team meeting time, reflective thinking, sentimental support, recognition of others, and solving problems by the time spending together. Third, the meanings of conflict experience in cooperative activity are formation of felt responsibility, self-growth through consideration of others, reciprocity, and recognition of the meaning of cooperation.

• Journal of The Korean Association of Information Education
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• v.22 no.3
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• pp.297-305
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• 2018

Physical computing is the concept of expanding computing to humans, environments, and objects. It draws attention as a programming learning medium based on physical outputs in integration of hardware and software. This study developed a programming learning model based on interactive prototyping using the characteristics of physical computing with a high degree of technical freedom and analyzed its learning effect in an experiment. To examine the effect of the experimental treatment, this researcher divided fifty nine 5th-grade elementary students into an experimental group and into a control group. the interactive prototyping programming learning model was applied to the experimental group, and a linear sequential programming learning model was applied to the control group. Information Science Creative Personality Test was conducted before and after the experimental treatment. Analysis of Covariance was conducted with the pre-test scores of the two groups. As a result, it was proved that there was the effect of learning at the significance level of .05. It indicates that the physical computing based interactive prototyping programming learning model is applicable to the programming learning for 5th-grade elementary students.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1107-1116
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• 2016

Recent astronomical survey observations have produced substantial amounts of data as well as completely changed conventional methods of analyzing astronomical data. Both classical statistical inference and modern machine learning methods have been used in every step of data analysis that range from data calibration to inferences of physical models. We are seeing the growing popularity of using machine learning methods in classical problems of astronomical data analysis due to low-cost data acquisition using cheap large-scale detectors and fast computer networks that enable us to share large volumes of data. It is common to consider the effects of inhomogeneous spatial and temporal coverage in the analysis of big astronomical data. The growing size of the data requires us to use parallel distributed computing environments as well as machine learning algorithms. Distributed data analysis systems have not been adopted widely for the general analysis of massive astronomical data. Gathering adequate training data is expensive in observation and learning data are generally collected from multiple data sources in astronomy; therefore, semi-supervised and ensemble machine learning methods will become important for the analysis of big astronomical data.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.100-100
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• 2023

단기 강우 예측에는 주로 물리과정 기반 수치예보모델(NWPs, Numerical Prediction Models) 과 레이더 기반 확률론적 방법이 사용되어 왔으며, 최근에는 머신러닝을 이용한 레이더 기반 강우예측 모델이 단기 강우 예측에 뛰어난 성능을 보이는 것을 확인하여 관련 연구가 활발히 진행되고 있다. 하지만 머신러닝 기반 모델은 예측 선행시간 증가 시 성능이 크게 저하되며, 또한 대기의 물리적 과정을 고려하지 않는 Black-box 모델이라는 한계점이 존재한다. 본 연구에서는 이러한 한계를 극복하기 위해 머신러닝 기반 blending 기법을 통해 물리과정 기반 수치예보모델인 Weather Research and Forecasting (WRF)와 최신 머신러닝 기법 (cGAN, conditional Generative Adversarial Network) 기반 모델을 결합한 Hybrid 강우예측모델을 개발하고자 하였다. cGAN 기반 모델 개발을 위해 1시간 단위 1km 공간해상도의 레이더 반사도, WRF 모델로부터 산출된 기상 자료(온도, 풍속 등), 유역관련 정보(DEM, 토지피복 등)를 입력 자료로 사용하여 모델을 학습하였으며, 모델을 통해 물리 정보 및 머신러닝 기반 강우 예측을 생성하였다. 이렇게 생성된cGAN 기반 모델 결과와 WRF 예측 결과를 결합하는 머신러닝 기반 blending 기법을 통해Hybrid 강우예측 결과를 최종적으로 도출하였다. 본 연구에서는 Hybrid 강우예측 모델의 성능을 평가하기 위해 수도권 및 안동댐 유역에서 발생한 호우 사례를 기반으로 최대 선행시간 6시간까지 모델 예측 결과를 분석하였다. 이를 통해 물리과정 기반 모델과 머신러닝 기반 모델을 결합하는 Hybrid 기법을 적용하여 높은 정확도와 신뢰도를 가지는 고해상도 강수 예측 자료를 생성할 수 있음을 확인하였다.

• Journal of Internet Computing and Services
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• v.5 no.2
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• pp.97-105
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• 2004

The reason that an intelligent agent cannot understand the representation of its own perception or activity is caused by the traditional syntactic approach that translates a semantic feature into a simulated string, To implement an autonomously learning intelligent agent, Cohen introduces a experimentally semantic approach that the system learns a contentful representation of physical schema from physically interacting with environment using its own sensors and effectors. We propose that negation is a meta-level schema that enables an agent to recognize its own physical schema, To improve the planner's efficiency, Graphplan introduces the control rule that manipulates the inconsistency between planning operators, but it cannot cognitively understand negation and suffers from redundancy problem. By introducing a negative function not, IPP solves the problem, but its approach is still syntactic and is inefficient in terms of time and space. In this paper, we propose that, to represent a negative fact, a positive atom, which is called opposite concept, is a very efficient technique for implementing an cognitive agent, and demonstrate some empirical results supporting the hypothesis.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.168-173
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• 2008

Recently, many researchers have studied on agent-based edutainment systems to improve students' learning experience. In this paper, we present AR Gardening which makes users experience interactive flower gardening with a bluebird, a learning companion agent, squatting in an augmented picture. The proposed system augments the animated bluebird to support interactive edutainment experiences. The bluebird perceives users' actions as well as environmental situations. It then appraises situational information to provide participants with problem-solving guidelines. Moreover, the bluebird responds like a companion than an instructor through anthropomorphic expression. To demonstrate our work, we exhibited the implemented AR Gardening and reviewed participants' responses to the system. In this exhibition, we could find that the learning companion-like bluebird helped users experience how to properly grow the flower in our educational setting. Ultimately, we expect that an augmented peer learning agent is one of the key factors for developing effective edutainment applications.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.8
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• pp.171-180
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• 2020

Smart Factory consists of digital automation solutions throughout the production process, including design, development, manufacturing and distribution, and it is an intelligent factory that installs IoT in its internal facilities and machines to collect process data in real time and analyze them so that it can control itself. The smart factory's equipment works in a physical combination of numerous hardware, rather than a virtual character being driven by a single object, such as a game. In other words, for a specific common goal, multiple devices must perform individual actions simultaneously. By taking advantage of the smart factory, which can collect process data in real time, if reinforcement learning is used instead of general machine learning, behavior control can be performed without the required training data. However, in the real world, it is impossible to learn more than tens of millions of iterations due to physical wear and time. Thus, this paper uses simulators to develop grid sortation systems focusing on transport facilities, one of the complex environments in smart factory field, and design cooperative multi-agent-based reinforcement learning to demonstrate efficient behavior control.

• The Journal of Korean Association of Computer Education
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• v.17 no.5
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• pp.25-34
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• 2014

The object of this study is to improve obstacles related with physical affordance and cognitive affordance by adopting Norman's theory for affordance of mobile application of museum education. As to conduct the study, I have selected the mobile device application of G museum for the need of observation and interviewing, and have applied think aloud protocol to analyse matters of affordance. By this study, learners will be possible to conduct appropriate behavior instantly under the circumstance of unfamiliar museum mobile environment because of sophisticated design to make learners perceive and understand information provided with designed interface based on realistic improvement that will be made by inspecting possible problems of affordance in position of museum education mobile system users. Additionally learners will be able to control contents of museum and to experience interactive learning which motivate exploratory activity to accomplish meaningful learning.